Potential energy surfaces and dissociation mechanisms of molecular ions

peer reviewe

Human-Machine Interaction Issues in Quality Control Based on Online Image Classification

This paper considers on a number of issues that arise when a trainable machine vision system learns directly from humans. We contrast this to the ldquonormalrdquo situation where machine learning (ML) techniques are applied to a ldquocleanedrdquo data set which is considered to be perfectly labeled with complete accuracy. This paper is done within the context of a generic system for the visual surface inspection of manufactured parts; however, the issues treated are relevant not only to wider computer vision applications such as medical image screening but also to classification more generally. Many of the issues we consider arise from the nature of humans themselves: They will be not only internally inconsistent but also will often not be completely confident about their decisions, particularly if they are making decisions rapidly. People will also often differ systematically from each other in the decisions they make. Other issues may arise from the nature of the process, which may require the ML to have the capacity for real-time online adaptation in response to users' input. Because of this, it may be that the users cannot always provide input to a consistent level of detail. We describe how all of these issues may be tackled within a coherent methodology. By using a range of classifiers trained on data sets from a compact disc imprint production process, we present results which demonstrate that training methods designed to take proper consideration of these issues may actually lead to improved performance

An on-line interactive self-adaptive image classification framework

In this paper we present a novel image classification framework, which is able to automatically re-configure and adapt its feature-driven classifiers and improve its performance based on user interaction during on-line processing mode. Special emphasis is placed on the generic applicability of the framework to arbitrary surface inspection systems. The basic components of the framework include: recognition of regions of interest (objects), adaptive feature extraction, dealing with hierarchical information in classification, initial batch training with redundancy deletion and feature selection components, on-line adaptation and refinement of the classifiers based on operators' feedback, and resolving contradictory inputs from several operators by ensembling outputs from different individual classifiers. The paper presents an outline on each of these components and concludes with a thorough discussion of basic and improved off-line and on-line classification results for artificial data sets and real-world images recorded during a CD imprint production process. © 2008 Springer-Verlag Berlin Heidelberg

Procedimiento de preparación de materiales superconductores texturados obtenidos por fusión zonal inducida por láser

Fecha de solicitud: 01.09.2000.- Consejo Superior de Investigaciones Científicas (CSIC).- Universidad de Zaragoza.[EN]Procedure for preparing textured superconductor materials obtained by laser-induced zone melting.Materials of the YBCO, Bi-2212 and Bi-2223 families are obtained from a ceramic using a laser zone melting system, including: a watertight growth chamber in which two mechanical extensions are housed to support the system for shaft transfer and rotation movement; two separate windows, made of quartz and of zinc selenide, which provide passage for the two lasers connected to the chamber, one Nd:YAG and the other CO2. Each laser focuses on the preform with two or more different shapes. The preforms are fastened to the shafts with various types of very small, commercially available clamps. These materials, given their textured microstructure, are useful in application such as power supply busbars, current limiter components, network filters, etc. [ES] Procedimiento de preparación de materiales superconductores texturados obtenidos por fusión zonal inducida por láser. Se obtienen materiales de las familias YBCO, Bi-2212 y Bi-2223, a partir de una cerámica y mediante un sistema de fusión zonal por láser, que incluye: una cámara de crecimiento estanca, donde se encuentran alojadas dos extensiones mecánicas que hacen de soporte del sistema de movimiento de traslación y rotación de ejes; dos ventanas distintas, de cuarzo y de seleniuro de cinc, que permiten el paso de dos láseres acoplados a la cámara, uno de Nd:YAG y otro de CO2. Cada láser se enfoca sobre la preforma de dos o más formas distintas. las preformas se sujetan sobre los ejes con diversos tipos de mordazas comerciales de tamaño muy reducido. estos materiales por su microestructura texturada les hace útiles en aplicaciones como barras de alimentación, componentes para limitadores de corriente, filtros de red, etc.Peer reviewe